Search
225 articles for “linearity of data”
-
Rapid Determination of Content of Etoricoxib in Pharmaceutical Formulations by Mid-Infrared Spectroscopy
Abstract: The present paper is an attempt to highlight a new technique FTIR-ATR along with its referenced validated method, UV spectrophotometric analysis. Different concentrations of etoricoxib were used as samples to draw standard plot. From different samples, a transmission spectrum was recorded according to the prominence of peaks. The present study has chosen the three most prominent peaks for analytical purpose in case of samples of etoricoxib and marketed formulations. All …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 4, Issue 3, 2013 · pp. 20–32 Read article
-
A Latest Approach for Crime Rate Prediction and Analysis by Using the Clustering and Machine Learning Algorithm
Abstract: In our daily life, the collection and analysis of crime-related data is uncertain from a security perspective. Crime rate forecasting and analysis is a way of identifying and analyzing crime patterns in crime data contained in a crime database. Our system predicts what criminal activity occurs in everyday life in various parts of the world. Through the utilization of machine learning and data mining algorithms, it is possible to forecast …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 32–42 Read article
-
Solitary Identification and Analysis of Considerate Nutritional Consumption and Identifying Malnutrition
Abstract: The food supply chain is in danger from various factors, including climate threats, such as heat waves, floods, droughts, and other extreme occurrences such as intensive livestock farming, demand for animal protein, practices for antimicrobial resistance and various other factors leading to serious food shortages and an increase in food prices. Malnutrition is a major issue, with an estimated 663 million individuals affected. Poor nutrition is a serious problem that …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 2, 2023 · pp. 46–62 Read article
-
Comparative Analysis of Neural Network and Linear Regression Applied to Black Friday Data
Abstract: AbstractIn this study, it compares two different types of neural networks. First is a single layer neural network and other is multiple hidden layer neural network. For just comparisons it is ensured that both uses the same activation and output functions and have the same number of nodes and parameters. The networks are trained by the gradient descent algorithm to approximate linear and quadratic functions and examine their convergence properties. …
Published in Current Trends in Signal Processing · Vol. 9, Issue 3, 2019 · pp. 1–4 Read article
-
Off-Line List Accessing Algorithms with Circular Doubly Linked List and Partial Cost Model
Abstract: List Accessing Problem (LAP) has been an interesting and challenging research area for computer scientists since last four decades. Various algorithms have been developed to access the records by different researchers with an intention to minimize the cost of traversal. This paper describes two newly proposed algorithms, which are variants of FC and MTF for circular doubly linked list with the use of partial cost model. A theoretical as well …
Published in Current Trends in Information Technology · Vol. 1, Issue 1, 2011 · pp. 16–22 Read article
-
House Price Prediction Using Linear Regression In Machine Learning
Abstract: In the modern world, real estate is among the most important investments, particularly in a city like Chennai, which is where many people aspire to work and settle down. Due to people's high purchasing power, this will cause property prices to rise daily. When purchasing a home, buyers will consider whether or not it will yield a healthy profit margin. Hence, before spending your hard-earned money on any property, it …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 92–100 Read article
-
Statistical and AI Approaches to Measure Sustainability Performance of Enterprises
Abstract: Measuring sustainability performance has become a critical priority for enterprises facing increasing regulatory pressure, stakeholder expectations, and global sustainability challenges. Traditional assessment methods, largely based on static indicators and manual reporting, often struggle to capture the multidimensional, dynamic, and data-intensive nature of sustainability. This study explores the integration of statistical and artificial intelligence (AI) approaches to evaluate and enhance the sustainability performance of enterprises in a more robust, accurate, and …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 30–36 Read article
-
An Overview of Artificial Neural Network and its Applications
Abstract: This paper presents an overview of Artificial Neural Network (ANN). The study of neurons and its discrete representation by the set theory is the key objective of this paper. New data structure technique is proposed in this paper by using the mechanism of (ANN). The finite dimension of the field is generalized in this paper. The linear transformation and the representation of the vector basis are applied to propose the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 2, 2020 · pp. 17–20 Read article
-
Environmental Impact Assessment of Ocean Energy Converters Using Quantum Machine Learning
Abstract: The accelerating deployment of ocean energy converters (OECs) across tidal, wave, osmotic, and thermal domains necessitates rigorous, data-intensive environmental impact assessment (EIA) frameworks capable of modelling multi-stressor marine ecosystems in real time. Classical machine learning approaches, while operationally mature, encounter scalability bottlenecks and feature correlation limitations when applied to the high-dimensional, non-linear datasets characteristic of offshore monitoring networks. This paper presents a comprehensive quantum machine learning (QML) framework for the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 1, 2026 · pp. 22–31 Read article
-
Arrays: Review
Abstract: This paper contains a description of the array data type and some discussion as to how we allocate memory space to arrays. The value of defining arrays as an abstract data type is primarily for systems programmers, who works behind the scenes and bring you all the wonderful software that comes with Operating systems such as; compilers, linkers, files managers, text editors, etc. For most of us mortal people, we …
Published in Recent Trends in Parallel Computing · Vol. 2, Issue 3, 2015 · pp. 24–26 Read article
-
Gradient Boosted Regression Tree Approach to Predicting Toxic Interactions on X and YouTube
Abstract: In the digital age, social media platforms play a vital role in facilitating user engagement, encompassing both positive interactions and avenues for negative, often harmful behaviors. Recognizing and addressing toxic exchanges is paramount to nurturing healthy online communities and preserving users’ well-being. This study introduces a novel method for identifying toxic interactions by utilizing Gradient Boosting Regression Trees (GBRT) algorithm, a machine learning approach renowned for its exceptional accuracy and …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 7–14 Read article
-
House Price Prediction: A Review
Abstract: In today’s scenario, real estate industry is growing rapidly. Everyone wants to purchase land and a home, either for personal use or as an investment. House prices keep changing day by day and it is hard for a person to choose the best from all of them. There are many technologies that help to analyse the various aspects of buying property. These digital platforms are created using various algorithms like …
Published in Journal of Open Source Developments · Vol. 9, Issue 3, 2022 · pp. 25–29 Read article
-
Dimensionality Reduction: A Brief Survey on Its Myriad Techniques
Abstract: This paper is a short survey and analysis on different techniques and methods using which efficiency of existing techniques can be improved which are used for data exploration, or search for those features which has deeper relationship amongst the variable, which relies on greater extent on visual methods. However, for multidimensional data set with real time data collected captured using sensors or real time applications, redundant and unused or wanted …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 6, Issue 2, 2017 · pp. 46–51 Read article
-
Stock Price Analysis and Forecasting Using Linear Regression and SVM Classifiers
Abstract: In this study, we attempt to implement a Machine Learning approach to predict stock market prices. Linear Regression is very effectively implemented in forecasting stock prices, returns, and stock modelling. This project is for common users as the prediction is done on all of the companies. We outline the design of the Linear Regression model with its salient features and customizable parameters. We select a certain group of parameters with …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 62–66 Read article
-
Regression Analysis of Research Data using R Programming
Abstract: ABSTRACTThe goal of the review paper is discussing the relationship between various types of regression analysis whose output was sufficiently analyzed using R programming. The primary purpose of this paper is to explain the relationship of linear, multiple, quantile and polynomial regression models to achieve final conclusion with different data sets. Therefore, this paper presents the easiest way of regression analysis commands and R programming strengths for of data analysis. …
Published in Recent Trends in Programming languages · Vol. 6, Issue 2, 2019 · pp. 42–50 Read article
-
Neural Network Machine Learning Analysis for Noisy Data: R Programming
Abstract: Abstract: This review paper clearly discusses the compression between Neural Network Machine Learning Analysis for Noisy Data: R Programming. Although there is large gap between data analysis to analyze overfitting and multicollinearity problems in data sets. Its primary purpose is to explain the machine learning procedures using neural network whose data structure were cross validation using R software whose outputs were sufficiently explain with various intermediate output and graphical interpretation …
Published in Recent Trends in Programming languages · Vol. 6, Issue 3, 2019 · pp. 1–10 Read article
-
Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
-
Soil Erosion Assessment and Its Effect on Sustainability for a Mountainous Watershed using Remote Sensing and GIS
Abstract: Normal 0 false false false EN-US X-NONE AR-SA Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 Soil erosion is an important social and economic problem, and an essential factor in assessing health and function of ecosystem. Soil-erosion control requires a quantitative evaluation of potential soil erosion on a specific location. The revised universal soil loss equation (RUSLE), remote sensing, and …
Published in Journal of Remote Sensing & GIS · Vol. 4, Issue 3, 2013 · pp. 68–80 Read article
-
Development and Validation of HPTLC Methods for Estimation of Trimebutine Maleate in Pharmaceutical Formulation
Abstract: A simple and rapid high-performance thin-layer chromatographic (HPTLC) method was developed and validated for quantitative determination of trimebutine maleate in single dose formulation. Trimebutine maleate was chromatographed on silica gel 60 F 254 TLC plate using methanol–toluene (8:2 v/v) as mobile phase. The plates were developed to a distance of 8 cm at ambient temperature. Trimebutine maleate was quantified by densitometric analysis at 271 nm. The method was found to …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 8, Issue 1, 2017 · pp. 17–22 Read article
-
The fundamental premises of efficient linear regression and applying Regression
Abstract: Linear regression is a statistical technique for estimating the value of a dependent variable from an independent variable. Linear regression is a way to assess how two variables are related.A dependent variable is predicted using this modelling technique based on one or more independent factors. Many analyses are based on linear regression. Sometimes the data must be changed to satisfy the needs of the analysis, or extra room must be …
Published in Trends in Machine design · Vol. 9, Issue 2, 2022 · pp. 21–26 Read article